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Recent Advance in Multi-Carrier Underwater Acoustic Communications
G. P. Harish Annamalai University, Tamilnadu, India
Abstract—underwater acoustic (UWA) channel is characterized as a severe multipath propagation channel due to signal reflections from the surface and the bottom of the sea and also a fast time-varying channel due to transceiver motion and medium inhomogeneities. Therefore, UWA communications have been regarded as the most challenging wireless communications. The Multi-carrier communication is a promising communication technique for future communication systems. In the past decade, much research literature focuses on deploying multi-carrier communications in UWA environments. This paper propose an overview of recent advance in multi-carrier UWA communications, which includes but not limited to Orthogonal Frequency Division Multiplexing (OFDM), Multi-input-MultiOutput (MIMO), and their related channel estimation and adaptive communications. Keywords- Underwater acoustic channel, OFDM, MIMO, Adaptive communications, Channel estimation.

In this paper, we propose an overview of multi-carrier communications in UWA environments. The content includes OFDM modulation-based channel estimation, OFDM and Multi-input-Multi-output (MIMO)-OFDM UWA communication systems, and their related adaptive communications. The rest of this paper is organized as follows: Section II is the introduction of OFDM communication systems. Section III is the overview of channel estimation for UWA communications. Section IV is the overview of recent advance in multi-carrier UWA communication systems. Section V is the conclusion of this paper. II. OFDM UWA COMMUNICATION

I.

INTRODUCTION

Signal propagation in underwater acoustic (UWA) environments will suffer severe multipath delay due to reflections from the sea surface and bottom. In addition, the UWA channel is a kind of fast time-varying channels due to surface wave and transceivers in motion, medium inhomogeneities and sound speed anomaly, and effect of wind-generated bubbles [1-3]. Therefore, UWA communications have been regarded as one of the most challenging wireless communication systems, especially in shallow water environments. How to achieve high data rate and reliable communications in UWA environment is one of challenging topics of wireless communications that has perplexed scientists for a long time. Multi-carrier communications is a promising technique that could increase the system capacity and data rate significantly. Orthogonal Frequency Division Multiplexing (OFDM) is a sophisticated multi-carrier technique, which has merits of robust overcoming multipath propagation delay via cyclic prefix (CP), mitigating inter-symbol interference (ISI) and inter-channel interference (ICI). Currently, OFDM has been adopted in the 4th generation wireless communication systems, Wireless LAN network, HDTV and so on [4]. However, OFDM applications in UWA communications are very scarce [5-7].

Figure 1 depicts eigen-ray propagation in UWA environments. Here, eigen-ray means acoustic wave path propagating from the transmitter side to the receiver side [8]. Figure 2 schematically depicts the structure of an OFDM UWA communication system. The key characteristics and principles of operation of OFDM communications include orthogonality, implementation using the FFT/IFFT algorithm, guard interval/cyclic prefix for elimination of ISI, simplified equalization, and so on [9].

Channel estimation techniques in UWA environments can be divided into two categories: deterministic approach and stochastic approach [10]. The deterministic approach regards the channel as a set of fixed unknown parameters to be estimated and solve a least squares estimation problem to recover the channel, while the stochastic approach exploits the second order statistics of the channels. The existing algorithms of these approaches find the proper correlation between both the time and frequency domain and linearly combine to reconstruct the channel state information (CSI) for the desired time and frequency slot. Since most of these algorithms exhibit high complexity, the applications and research of statistics approaches in UWA environments are scarce due to the difficulty of tracking fast time-varying channels. In the following of this section, we propose an overview of channel algorithms for the deterministic approach and stochatic approach, respectively. In the deterministic approach, the channel estimator, such as Least Square (LS) and Minimum Mean Square Error (MMSE), and pilot signal are required for OFDM channel estimations. [11] proposed pilot-aided OFDM channel estimations, which involve in the block-type and comb-type pilots for OFDM systems. Authors prove that the proposed channel estimators can work effectively in both time and frequency domains for tracking fast time-varying UWA channels. [10] proposed efficient channel estimation schemes for OFDM systems in UWA environments. A robust channel estimator using pilot symbol assisted modulation (PSAM) for both single-input and single-output (SISO) and MIMO system is developed which provides excellent performance, good spectrum efficiency and manageable complexity. In [12], frequency and time correlation of the UWA channel were exploited to obtain a low-complexity adaptive channel estimation algorithm for multiple-input–multiple- output (MIMO) spatial multiplexing of independent data streams. The algorithm is coupled with non-uniform Doppler prediction and tracking, which enable decision-directed operation and reduces the overhead. In [13], the performance of three pilot

patterns and their own application conditions are analyzed and compared. According to the simulation and experiment results, it is concluded that scatter pilot pattern is very suitable for OFDM system for underwater acoustic communications. Besides, the other deterministic algorithms with significant performance, they can be found in [14-16]. In the stochastic approach, [17] considered UWA channel estimation based on sparse recovery using the recently developed homotopy algorithm. The UWA communication system under consideration employs OFDM and receiver preprocessing to compensate for the Doppler Effect before channel estimation. [18] provided a novel UWA Channel estimation and Simulator based on measured scattering functions. In addition to these two categories, there is much literature engages in establishing effectively channel estimation methods for OFDM UWA communications. [19] investigated two methods for estimating the matched signal transformations caused by time-varying UWA channels in OFDM communication systems. The first channel estimation method is based on discretizing the wideband spreading function timescale representation of the channel output using the Mellin transform. The second method is based on extracting the timescale features of distinct ray paths in the received signal using a modified matching pursuit decomposition algorithm. IV. RECENT ADVANCE IN MULTI-CARRIER UWACOMMUNICATIONS

A. OFDM UWA Communications We discuss several important issues of OFDM UWA communications. Due to unique properties of UWA channels, OFDM UWA communication systems have many different points compared with radio frequency OFDM communications. [20] applied OFDM to realize parallel transmission of spread spectrum signal in UWA communications, so as to provide robust acoustic links or long distance communication abilities. The traditional CP-based OFDM communications using a overlap-add method have a bad performances when channel is severe frequency-selective, especially with channel nulls, which is often encountered in UWA channels, [21] utilized zero-padding (ZP)-OFDM channel equalization on the premise of the channel transfer matrix is Toeplitz matrix, Monte-Carlo simulation proved that this method has a better performance than CP-OFDM, and has a good application prospect for UWA communications. [22] presented a desirable property of OFDM that one signal design can be easily scaled to fit into different transmission bandwidths with negligible changes on the receiver. Doppler Shift is an important factor that affects the performance of UWA communication systems. Therefore, how to overcome the Doppler Shift problem in OFDM UWA communications becomes a challenging issue. [23] focused on ZP-OFDM to minimize the transmission power. In addition, authors treated the channel as having a common Doppler scaling factor on all propagation paths, and propose a two-step approach to mitigating the Doppler effect: (1) non-uniform

Doppler compensation via resampling that converts a "wideband" problem into a "narrowband" problem and (2) high-resolution uniform compensation of the residual Doppler. [24] studied the performance of OFDM over UWA multipath channels with different Doppler scales on different paths. [25] treated the channel as having a common Doppler scaling factor on all propagation paths, and propose a novel approach to mitigating the Doppler effects in OFDM UWA communication systems. Mitigation of ICI and ISI of OFDM UWA communication systems is another challenging issue for achieving high data rate and reliable communications. [26] focused on CP-OFDM over time-varying UWA channels. To cope with the ICI that arises at the receiver side because of the time variations in the channel, authors considered two ICI-mitigation techniques. In the first scheme, the ICI coefficients are explicitly estimated, and minimum mean square error linear equalization based on such estimates is performed. In the second approach, no explicit ICI estimation is performed, and detection is based on an adaptive decision-feedback equalizer applied in the frequency domain across adjacent subcarriers. Real implementations and performance analysis of OFDM UWA communication systems have been investigated by many researchers. [27] designed and implemented the OFDM signal transmitter with FPGA (field programmable gate array) and DSPs (digital signal processor, ADSP-TS101). [28-28] analyzed the performance of capacity criterion-based OFDM UWA communications. Above all, [29] derived bounds to the channel capacity of OFDM systems over the UWA fading channel as a function of the distance between the transmitter and the receiver. The upper bound is obtained under perfect CSI at the receiver. The lower bound is obtained assuming the input is drawn from phase-shift keying (PSK) constellation which results in non-Gaussian distribution of the output signal and no CSI. B. MIMO-OFDM UWA Communications The MIMO-OFDM scheme is one kind of more advance communication technique for UWA communications. MIMOOFDM could further increase the system capacity and data rate over the bandwidth limited channels. [30-31] presented a MIMO system design, where spatial multiplexing is applied with OFDM signals. The proposed receiver works on a blockby-block basis, where null subcarriers are used for Doppler compensation, pilot subcarriers are used for channel estimation, and a MIMO detector consisting of a hybrid use of successive interference cancellation. [32-33] provided further results of MIMO-OFDM UWA Communications. [34] analyzed MIMO-OFDM communications for shallow water environments, which is more challenging than normal UWA communication systems. C. Adaptive Multi-Carrier UWA Communications UWA communications possess properties of several channel fading and limited bandwidth resource. Therefore, adaptive techniques are more valuable to be adopted in UWA communications, especially for shallow water environments. In order to achieve adaptive signal transmission, information

Recent Advance in Multi-Carrier Underwater Acoustic Communications

Description

Underwater acoustic (UWA) channel is characterized as a severe multipath propagation channel due to signal reflections from the surface and the bottom of the sea and also a fast time-varying channe...

Underwater acoustic (UWA) channel is characterized as a severe multipath propagation channel due to signal reflections from the surface and the bottom of the sea and also a fast time-varying channel due to transceiver motion and medium inhomogeneities. Therefore, UWA communications have been regarded as the most challenging wireless communications. The Multi-carrier communication is a promising communication technique for future communication systems. In the past decade, much research literature focuses on deploying multi-carrier communications in UWA environments. This paper propose an overview of recent advance in multi-carrier UWA communications, which includes but not limited to Orthogonal Frequency Division Multiplexing (OFDM), Multi-input-Multi-Output (MIMO), and their related channel estimation and adaptive communications.